Improved Thermal Transmittance Measurement with HFM Technique on Building Envelopes in the Mediterranean Area

Abstract Although the designed theoretical value of U can be derived from the thermal parameters of layers composing an opaque element, according to ISO 6946:2007, measurements are necessary to confirm the expected behaviour. Currently, the measurements of thermal transmittance based on Heat Flow Meter method (HFM) and according to standard ISO 9869-1:2014 are widely accepted. Anyway, some issues related to difficulties in measurements are present: the roughness of wall surfaces, the proper contact between the heat flow plate and the temperature probes with wall surfaces, undesired changes in weather conditions. This work presents the results obtained in thermal transmittance measurements with a modified HFM method, widely described in this paper. Differences between U-values obtained with the modified HFM method and theoretical ones were in the range 0.6 - 6.5 %. Moreover, the modified HFM method provided a result closer to the theoretical one, when compared to that obtained with standard HFM method (discrepancy with theoretical value were 0.6% and 16.4%, respectively)

How to Identify the Recommended Number of Cores?

The concrete strength assessment process is influenced by uncertainties at many levels, including random measurement errors, sampling uncertainty and identification of the conversion model parameters. Therefore, instead of estimating the true value of the concrete strength, it is preferable to say that the objective of the assessment process is to predict a strength value ranging at a tolerable distance from the true strength value. This implies a deep revision of the assessment paradigm, in which both the acceptable tolerance interval and the risk of a wrong assessment must be given at the very beginning of the investigation. A large series of simulations has been carried out in order to understand and quantify how, for a given tolerance on the strength estimation, the risk value varies as a function of the precision of measurements, the number of cores and the strength distribution. Empirical models have been identified from the simulation results. These models have been finally used to calculate how many cores are required in various situations, to achieve the accuracy corresponding to three different estimation quality levels. This chapter describes the principles of the simulation, and how their results were used in order to build a series of tables where the recommended number of cores is made available in a variety of situations

Identification of Test Regions and Choice of Conversion Models

The main objective of test region (TR) identification is to define an efficient conversion model. The first part of the chapter aims a difficult question, the identification of test regions (TR) because each structure is specific and so it is impossible to give a unique methodology. Here, three different possibilities are proposed. The first one is based on synthetic data obtained on a continuous structure for which TR are identified by means of k-means clustering method. The second approach concerns a real building for which TR are determined by means of two different statistical methods based on the analysis of confidence interval and ANOVA. On three real case studies, the second part of the chapter compares the performances of two scenarios, either the consideration of several TRs and so a conversion model on each one, or the consideration of a unique TR with only one model. The efficiency of each scenario is quantified by the error on the estimation of both mean strength and local strength

How Investigators Can Assess Concrete Strength with On-site Non-destructive Tests and Lessons to Draw from a Benchmark

A benchmark is carried out in order to compare how 13 experts define and can carry out an NDT investigation program and derive strength values from NDT measurements. The benchmark is based on simulations, which reproduces a synthetic data set corresponding to a grid of twenty 3m-high columns defining the structure of a building made up of beams and columns. The experts must assess the mean and the standard deviation of compressive strength. Three levels of assessment are considered corresponding to different quantities of test results (destructive or non destructive) available for the experts. The comparison of the various strategies used by the experts and the analysis of results enables the identification of the most influential parameters that define an investigation approach and influence its efficiency and accuracy. A special emphasis is placed on the magnitude of the measurement error. A model of the investigation strategy is also proposed

How Investigators Can Answer More Complex Questions About Assess Concrete Strength and Lessons to Draw from a Benchmark

This benchmark aims to assess mean compressive strength at several scales and to identify the location and characteristics of possible weak areas in the structure. It concerns synthetic data simulated on a group of four concrete cylindrical structures of identical dimensions with different kinds of strength distribution, based on a real case study. After having received the test results corresponding to their request (non-destructive or destructive), all the experts have to analyze these data and assess the concrete properties and to localize possible weak areas. In addition, they have to define their assessment methodology, i.e. level of investigation, number, type and location of measurements. This study provides information about how the accuracy of the final estimates depend on choices done at the various steps of the assessment process, from the definition of the testing program to the final delivery of strength estimates

In-Situ Strength Assessment of Concrete: Detailed Guidelines

Guidelines describe the general process of in-situ compressive strength assessment. This process is divided into three main steps, data collection (using nondestructive testing and destructive testing), model identification and strength assessment. Three estimation quality levels (EQL) are defined depending on the targeted accuracy of strength assessment, based on three parameters, mean value of strength and standard deviation of strength on a test region and local value of strength. All the necessary definitions (test location, test reading, test region, test result, …) are given and the different stages of data collection, i.e. planning, NDT methods, cores (dimensions, conservation, location, testing, etc) are described. The identification of the conversion model is detailed and a specific attention is paid to the assessment of test result precision (TRP). For the identification of the model parameters, two options are considered either the development of a specific model or the calibration of a prior model. A specific option is also proposed, namely the bi-objective approach. Finally, the quantification of the errors of model fitting and strength prediction is described. The global methodology is synthetized in a flowchart